A multiscale description of growth and transport in biological tissues
Bibliographic record
Abstract
We study a growing biological tissue as an open biphasic mixture with mass exchange between phases. The solid phase is identified with the matrix of a porous medium, while the fluid phase is comprised of water, together with all the dissolved chemical substances coexisting in the pore space. We assume that chemical substances evolve according to transport mechanisms determined by kinematical and constitutive relations, and we propose to consider growth as a process able to influence transport by continuously varying the thermo-mechanic state of the tissue. By focusing on the case of anisotropic growth, we show that such an influence occurs through a continuous rearrangement of the tissue material symmetries. In order to illustrate this interaction, we restrict ourselves to diffusion-dominated transport, and we assume that the time-scales associated with growth and the transport process of interest are largely separated. This allows for performing an asymptotic analysis of the "field equations" of the system. In this framework, we provide a formal solution of the transport equation in terms of its associated Green's function, and we show how the macroscopic concentration of a given chemical substance is "modulated" by anisotropic growth. .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".